InternScience
partialShows if the model has enough results for an index.Agents-A1-4B
Agents-A1-4B is a reasoning model from InternScience in the Agents-A1 family. 7 benchmarks count toward its score, in 3 categories.
IndexOverall score out of 100.Unranked
CoverageShare of the index weight with results.45%
SpeedOutput tokens per second.—
Input / 1MUS dollars per 1M input tokens.Free
Output / 1MUS dollars per 1M output tokens.Free
ContextMaximum tokens in one request.262K
EloLMArena rating and rank.N/A
The index is a score out of 100. The ± range shows how much it can change.
CapabilitiesScore per category, out of 100.
Out of 100Results
7 counted| BenchmarkThe test name. | CategoryThe capability that the test measures. | ResultThe score from the publisher. | IndexThis result as a score out of 100. | RunThe settings of the run. | DateDate of the result. | Published byThe source of the result. |
|---|---|---|---|---|---|---|
| General AI Assistants | Agentic | 95.1% | — | — | — | Benchmark authors |
| Instruction-Following Eval | Instruction | 94.8% | 55.5 | — | — | Jeffrey Zhou et al. |
| τ²-Bench Tool-Agent-User Evaluation | Agentic | 78.2% | 54.9 | — | — | Victor Barres et al. |
| Instruction Following Benchmark | Instruction | 69.1% | 46.5 | — | — | Benchmark authors |
| BrowseComp | Agentic | 66.8% | 56.0 | — | — | OpenAI |
| LiveCodeBench v6 | Coding | 59.6% | 31.3 | — | — | LiveCodeBench maintainers |
| LongBench v2 | Reasoning | 52.1% | — | — | — | LongBench v2 authors |
| VITA-Bench | Agentic | 40.3% | 56.4 | — | — | Meituan LongCat Team |
| FrontierScience Research | Knowledge | 33.3% | — | — | — | Meta AI |
| Scientific Code Benchmark | Coding | 29.6% | 38.8 | — | — | Benchmark authors |
| MLE-Bench Lite | Agentic | 22.7% | — | — | — | MiniMax |
7 benchmarks count, from 7 of 11 results. A grey row does not count. Too few models took that benchmark.